The digital representation of data has advanced the efficient and widespread distribution of information. This enhanced availability is, in general, desirable. However, facile access to data also presents an increased opportunity for copyright violation. The possibility of unauthorized use of such widely available data has created a demand for reliable and economical methods for incorporating and detecting signature information in data amenable to electronic distribution. Such a signature could be used, for example, to mark photographs or other types of images as proprietary material before electronic publication or distribution through on-line services. The presence of the signature in a suspect image may serve, for example, to verify illegitimate use of that image. Also, different versions of the same image may be marked with different signatures to identify different routes of distribution.
Data hiding is a class of processes used to embed recoverable (e.g., signature) data in digitally represented information, such as a host image, with minimal degradation to the host information. Although the changes introduced by embedded data may be perceptible by a human observer, they need not be conspicuous or objectionable. The goal of data hiding is not to restrict access to the host information, but rather to make it impossible to distribute the host information without the embedded data. The ability to embed inconspicuous data makes data hiding attractive for adding signature information in images.
It is to be anticipated that after receiving the signature information, the encoded image will undergo intentional and inadvertent modification due, for example, to channel noise, filtering, resampling, rotation, cropping, lossy compression, or digital-to-analog (or analog-to-digital) conversion. In order to be effective, the data hiding technique should embed the signature information in a manner that allows determination of its presence or absence even after such modifications. For the present application, it is especially important that the technique also be resistant to attempts by an unauthorized user to obscure or eliminate the embedded data.
Many known data-hiding techniques are deficient in that the embedded data is not resistant to removal by lossy compression, e.g., by JPEG coding, one of the most widely used of such techniques for still images. The JPEG method applies a discrete cosine transform ("DCT"), closely related to a discrete Fourier transform, to nonoverlapping blocks of the image. A quantizer value is then applied to each coefficient of the transform to perform frequency-adaptive weighting. The weighting removes subjective redundancies in the image in order to optimize the visual quality of the decoded image for a given bit rate. The human visual system is less sensitive to reconstruction errors related to luminance variations of high spatial frequency than to those of low spatial frequency. JPEG's emphasis on preserving low DCT coefficients at the expense of higher ones exploits this differential sensitivity.
One class of techniques that is known to resist JPEG is direct-sequence modulation spread-spectrum methods. These embed data by adding to the host information a composite signal formed by linearly modulating a sequence of pseudo-random numbers onto a sequence of code signals. Decoding includes correlation of the test image data with the composite signal. These techniques allow direction of embedded data to frequency ranges that are less likely to be attenuated by anticipated future processing, and so can avoid loss of the data by lossy compression. Also, because decoding requires knowledge of the added composite signal, the embedded data is difficult to detect and deliberately remove. Nonetheless, decoding is problematic because it requires exact pixel-wise registration of the test image with the host image. Efficacious testing of an image that has been subjected to modifications such as filtering, cropping, rotation, or resealing would require complete knowledge of the details of the modification.